Innovations in electronics and technology have made it possible to incorporate a variety of advanced features on automotive vehicles. Various sensing technologies have been developed for detecting objects or monitoring the surroundings in a vicinity or pathway of a vehicle. Such systems are useful for parking assist, lane departure detection and cruise control adjustment features, for example.
More recently, automated vehicle features have become possible to allow for autonomous or semi-autonomous vehicle control. Sensors for such systems may incorporate LIDAR (light detection and ranging) or RADAR for detecting an object or another vehicle in the pathway of or otherwise near the vehicle. Depending on the approach speed, the cruise control setting may be automatically adjusted to reduce the speed of the vehicle based on detecting another vehicle in the pathway of the vehicle, for example.
One proposal to improve such sensing technologies includes using a multiple-input-multiple-output (MIMO) signaling technique that includes multiple, simultaneous signal transmissions. There are known ways to modulate such signals so that the different signals can be distinguished from each other at a receiver. One modulation technique includes a distinct modulation code for each signal. The codes allow for distinguishing the different signals from each other at the receiver in a known manner.
One difficulty introduced by MIMO techniques is the residue or noise associated with the multiple signal reception. Such residue reduces the signal-to-noise ratio and decreases the dynamic range of the device or system. It would be useful to be able to reduce the effect of such residue so that the other advantages of MIMO techniques can be realized with an automotive sensing device. Previously proposed approaches to removing or reducing the effects of such residue tend to be too computationally expensive and require too much processor capacity to be included on automotive vehicles.